Discovering Cure Hub Genes of Chromophobe Cell Renal Carcinoma Using weighted gene co-expression network analysis (WGCNA) and the Cure Defective Models

Abstract Renal cell carcinoma (RCC) is a common type of malignant tumor in the urinary system, with a high incidence rate and poor prognosis. It is frequently observed that a substantial proportion of patients who respond favorably to treatment appear to be free of symptoms in long-term follow- up and may be regarded as ‘cured.’ This study aimed to identify key genes and pathways associated with RCC using WGCNA and the 3-parameter defective Gompertz model as a cure model for identifying targeted therapeutic genes. Six key modules and genes related to cancer stage, pathology, metastasis, status, and overall survival were identified using WGCNA, and hub genes were identified using the PPI network. Two methods, Cox regression and the defective Gompertz model, were used to identify survival-related genes (SRGs) and cured survival-related genes (CSRGs) in RCC. Of the hub genes identified by two survival methods, 10 were common between the defective 3- parameter Gompertz and Cox models. six genes (NCAPG, TTK, DLGAP5, TOP2A, BUB1B, and BUB1) of them exhibited the highest area under the curve (AUC) values. Additionally, the defective 3-parameter Gompertz model calculated the min and max expression values for the cure rate, and it was found that six genes (TTK, KIF20A, DLGAP5, BUB1, AURKB, and CDC45) exhibited a strong reduction in the cure rate at their maximum expression levels. The results suggest that targeting these genes may hold promise as potential therapeutic strategies for improving treatment outcomes in RCC patients. The identified hub genes also showed excellent prognostic value and potential use as diagnostic biomarkers. This study provides new insights into the molecular mechanisms underlying RCC and highlights the potential clinical significance of targeting specific genes and pathways using the defective 3-parameter Gompertz model.